摘要
提出一种用模糊神经网络来进行数据挖掘的方法。把输入量进行模糊分类后,对神经网络进行训练,用误差反传的算法对神经网络的权值进行修正,并提出利用阀值来筛选规则,来得到有效的规则。最后通过一项实例来验证方法的有效性。
This paper presents a data mining method based on fuzzy neural network. After classifying the inputs by fuzzy theory, we can train the neural networks through revising the parameters with back propagation arithmetic, and get the effective rules by the use of a certain limited value. At last, an instance verifies the validity of the method.
出处
《微电子学与计算机》
CSCD
北大核心
2005年第12期48-50,54,共4页
Microelectronics & Computer
关键词
数据挖掘
模糊神经网络
误差反传
规则筛选
Data mining, Fuzzy neural network, Back propagation, Rule extraction